Sonia Garcia-Salicetti

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1 over the Internet, 2 in an office environment with desktop PC, and 3 in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

BIOMET: a multimodal person authentication database including face, voice, fingerprint, hand and signature modalities

Information technology innovations involve a constant evolution of man-machine interaction modes. Automated authentication of people could be used to better adapt the machine to the user. Security can also be enhanced through a better people authentication. Biometrics appears as a promising tool in these two situations. Different modalities can be envisaged, such as: fingerprint, human face images, hand shape, voice, handwritten signature... In order to take advantage of the particularities of each modality, and to improve the performance of a person authentication system, multimodality can be applied. This motivated the recording of BIOMET, a biometric database with five different modalities, including face, voice, fingerprint, hand and signature data. In this paper, the BIOMET multimodal database for person authentication is described. Details about the acquisition protocols of each modality are given. Preliminary monomodal verification results, obtained on a subcorpus of the BIOMET fingerprint data, are also presented.

On Using the Viterbi Path Along With HMM Likelihood Information for Online Signature Verification

This paper describes a system using two complementary sorts of information issuing from a hidden Markov model (HMM) for online signature verification. At each point of the signature, 25 features are extracted. These features are normalized before training and testing in order to improve the performance of the system. This normalization is writer-dependent; it exploits only five genuine signatures used to train the writer HMM. A claimed identity is confirmed when the arithmetic mean of two similarity scores, obtained on an input signature, is higher than a threshold. The first score is related to the likelihood given by the HMM of the claimed identity; the second score is related to the segmentation given by such an HMM on the input signature. A personalized score normalization is also proposed before fusion. Our approach is evaluated on several online signature databases, such as BIOMET, PHILIPS, MCYT, and SVC2004, which were captured under different acquisition conditions. For the first time in signature verification, we show that the fusion of segmentation-based information generated by the HMM with likelihood-based information considerably improves the quality of the verification system. Finally, owing to our two-stage normalization (at the feature and score levels), we show that our system results in more stable client-score distributions across databases and in a better separation between the distributions of client and impostor scores.

A new probabilistic Iris Quality Measure for comprehensive noise detection

In this article, we present a novel probabilistic iris quality measure based on a Gaussian mixture model (GMM). We compare its behavior to that of other standard iris quality metrics on two different types of noise which can corrupt the iris texture: occlusions and blurring. In the case of occlusions, we compare our GMM-based quality measure to an active contour method for eyelids and eyelashes detection. Finally, in the case of iris blurring, we compare our quality measure to a standard method based on Fourier transform and wavelets. For the latter, we have developed a new method to detect blur suitable for iris images. In our tests, we have used the ICE 2005 database and OSIRIS, an iris reference system based on the classical approach proposed by Daugman and developed in the framework of BioSecure European Network of Excellence for comparative evaluation purposes. Experiments show a significant improvement of performance when our GMM- based quality measure is used instead of the classical methods above mentioned. In particular, results show that this probabilistic quality measure based on a GMM trained on good quality images is independent from the kind of noise involved.

Iris identification using wavelet packets

We present a new method for iris identification particularly convenient for visible light images. It relies on the use of packets of wavelets (A. Laine and J. Fan, Nov. 1993) for the production of an iris code. Experiments, conducted on a database of 700 iris images, acquired with visible light illumination, show an improvement of 2% of FAR and of around 11.5% of FRR with the proposed method relatively to the classical wavelet method (J. Daugman, May 1995). The contribution of colour information is also studied with such method.

Fingerprint and On-Line Signature Verification Competitions at ICB 2009

This paper describes the objectives, the tasks proposed to the participants and the associated protocols in terms of database and assessment tools of two competitions on fingerprints and on-line signatures. The particularity of the fingerprint competition is to be an on-line competition, for evaluation of fingerprint verification tools such as minutiae extractors and matchers as well as complete systems. This competition will be officialy launched during the ICB conference. The on-line signature competition will test the influence of multi-sessions, environmental conditions (still and mobility) and signature complexity on the performance of complete systems using two datasets extracted from the BioSecure database. Its result will be presented during the ICB conference.

The Viterbi algorithm at different resolutions for enhanced iris segmentation

We propose in this paper a novel method for iris segmentation. In order to retrieve iris contours, the Viterbi algorithm is applied on the gradient map of images processed by Anisotropic Smoothing. The Viterbi algorithm is exploited at two resolutions: at a high resolution, it allows finding precise contours, while at a low resolution, coarse contours that improve the accuracy of normalization circles are retrieved. We tested the method on several databases (ICE 2005, NDIRIS-0405, Casia-V3-Interval). Our extensive experiments on such databases lead to performance at the state of the art, while the proposed method does not require a refined parameter adaptation to the various degradations encountered.

Tuning cost and performance in multi-biometric systems: A novel and consistent view of fusion strategies based on the Sequential Probability Ratio Test (SPRT)

In this paper we propose a novel sequential score fusion strategy for multi-biometric systems. The strategys aim is to reduce the cost of a multi-biometric system by dynamically fusing the optimal number of systems required to take the final decision. This way we optimise at the same time cost and performance in the system. The novelty of this paper lies in the automatic tuning of the decision parameters (thresholds) at a desired level of performance by revisiting the Sequential Probability Ratio Test (SPRT).

On assessing the robustness of pen coordinates, pen pressure and pen inclination to time variability with personal entropy

In this work, we study different combinations of the five time functions captured by a digitizer in presence or not of time variability. To this end, we propose two criteria independent of the classification step: Personal Entropy, introduced in our previous works and an intra-class variability measure based on Dynamic Time Warping. We confront both criteria to system performance using a Hidden Markov Model (HMM) and Dynamic Time Warping (DTW). Moreover, we introduce the concept of short-term time variability, proposed on MCYT-100, and long-term time variability studied with BIOMET database. Our experiments clarify conflicting results in the literature and confirm some other: pen inclination angles are very unstable in presence or not of time variability; the only combination which is robust to time variability is that containing only coordinates; finally, pen pressure is not recommended in the long-term context, although it may give better results in terms of performance (according to the classifier used) in the short-term context.

Biosecure reference systems for on-line signature verification: a study of complementarity

In this paper, we present an integrated research study in On-line Signature Verification undertaken by several teams that participate in the BioSecure Network of Excellence. This integrated work started during the First BioSecure Residential Workshop, has as main objective the development of an On-line Signature Verification evaluation platform. As a first step, four On-line Signature Verification Systems based on different approaches are evaluated and compared following the same experimental protocol on MCYT signature database, which is the largest existing on-line western signature database publicly available with 16500 signatures from 330 clients. A particular focus of work documented in this paper is multi-algorithmic fusion in order to study the complementarity of the approaches involved. To this end, a simple fusion method based on the Mean Rule is used after a normalization phase.RésuméDans cet article, nous présentons un travail commun sur la vérification de signature enligne, réalisé par 4 équipes qui participent au Réseau d’Excellence BioSecure. Ce travail commun, débuté durant le premier « Workshop » résidentiel, a pour principal objectif le développement d’une plateforme d’évaluation pour la vérification de la signature en-ligne. Tout d’abord, quatre systèmes de vérification de signature en-ligne basés sur différentes approaches sont évalués et comparés en utilisant le même protocole expérimental sur la base de signatures MCYT, la plus grande base existante de signatures en-ligne disponible, avec 16500 signatures de 330 personnes. Ensuite, l’accent est mis sur la fusion multi-algorithmique afin d’étudier la complémentarité des approches impliquées. Pour cela, une méthode de fusion simple est utilisée, basée sur une moyenne des scores après une phase de normalisation.